As defined in ISO 11179 , a value domain is a set of permissible values. Another way to think about value domains is within the concept of infinite space, which we define as every possible combination of Unicode alphanumeric characters. Each term contains values collectively derived from a specific combination(s) of characters within the larger infinite space. Values domains were created to address a need to define the combinations. Over time, commonalities between value domains provided the criteria to further categorize them based on the nature of the mechanism (e.g., fixed list and text pattern).
|Enumerated||Fixed list of all permissible values||Gender: [m, f, o] Commonly referred to as lookup tables, picklists, and valid value sets|
|Described||Value domain defined by one or more expressions, patterns, or formats that values must adhere too||date, URL, email address||Also referred to as non-enumerated domains|
|Range||Defines the upper and lower bounds of a number using a maximum and minimum numeric value||-180 > n < 180 (latitude)||Only applies to numeric data types|
|Boolean||The specific pair of binary values used by a term with boolean data type||[0,1], [true/fals]||Where not explicitly defined, the boolean value domain is assumed to be true/false which adheres to the JSON Specification|
Conceptual domains are sets of value meanings commonly presented using a list of concepts or descriptions. They describe the set of concepts that can be represented within a data element. 'US States' is an example, which describes the set of concepts (the geopolitical units comprising the United States) but does not specify their values (the actual state names or abbreviations). Most conceptual domains are associated with one or more value domains (e.g., US States by region, where the meaning remains the same, but the fixed list changes). In contrast, the associated value domain contains the actual names of the states (which is technically an enumerated domain since the list is fixed). 
 ISO/IEC 11179-1:2015(en) Information technology — Metadata registries (MDR) — Part 1: Framework (https://www.iso.org/obp/ui/#iso:std:iso-iec:11179:-1:ed-3:v1:en)
 Loshin, D. (2011) The Practitioner's Guide to Data Quality Improvement. Morgan Kaufmann Publishers Inc. https://doi.org/10.1016/C2009-0-17212-4